Quantization of Binary-Input Discrete Memoryless Channels
Quantization of Binary-Input Discrete Memoryless Channels
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DOI：
10.1109/tit.2014.2327016
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发表时间：
2014-08-01
影响因子：
2.5
通讯作者：
Yagi, Hideki
中科院分区：
文献类型：
--
作者：
Kurkoski, Brian M.;Yagi, Hideki
将二值输入离散无记忆信道的输出量化到更小的电平。给出了在信道输入和量化器输出间互信息最大化的情况下寻找最优量化器的算法。这一结果适用于任意通道，而之前的结果适用于受限通道或受限数量的量化器输出。在最坏的情况下，算法复杂度为通道输出数m的三次M-3。使用Burshtein， Della Pietra， Kanevsky和Nadas的映射定理证明了最优性，该定理最小化了分类和回归树的平均杂质。
The quantization of the output of a binary-input discrete memoryless channel to a smaller number of levels is considered. An algorithm, which finds an optimal quantizer, in the sense of maximizing mutual information between the channel input and quantizer output is given. This result holds for arbitrary channels, in contrast to previous results for restricted channels or a restricted number of quantizer outputs. In the worst case, the algorithm complexity is cubic M-3 in the number of channel outputs M. Optimality is proved using the theorem of Burshtein, Della Pietra, Kanevsky, and Nadas for mappings, which minimize average impurity for classification and regression trees.